https://github.com/AmirmohammadRostami/KeywordsSpotting-EfficientNet-A0
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.
In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.
Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Learning Transferable Visual Models From Natural Language Supervision
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
MoViNets: Mobile Video Networks for Efficient Video Recognition
Video Classification with Channel-Separated Convolutional Networks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
A Closer Look at Spatiotemporal Convolutions for Action Recognition
Adaptive and Iteratively Improving Recurrent Lateral Connections
Temporal Convolutional Networks for Action Segmentation and Detection
A Closer Look at Spatiotemporal Convolutions for Action Recognition
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Rethinking Motion Representation: Residual Frames with 3D ConvNets for Better Action Recognition
Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
Real-time Hand Gesture Detection and Classification Using Convolutional Neural Networks
Make Skeleton-based Action Recognition Model Smaller, Faster and Better
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Real-Time Action Detection in Video Surveillance using Sub-Action Descriptor with Multi-CNN
TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity Recognition
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Learning Character-Agnostic Motion for Motion Retargeting in 2D
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.